Maia Angelova

• PhD, MSc, BSc Physics
• Professor at Aston University

Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chronic (cLBP). Whilst multi-factorial, the relative importance of contributors to cLBP remains unclear. We leveraged a comprehensive multi-dimensional data-set and machine learning-based variable importance selection to identify the most effective modali...

Assessing team performance in association football (commonly known as football or soccer) is challenging due to the sport’s low-scoring nature and inherent unpredictability. While evaluating strategies based on space control and the creation of open spaces has been explored in the literature, the temporal aspect of space availability for the ball c...

In association football, predicting the likelihood and outcome of a shot at a goal is useful but challenging. Expected goal (xG) models can be used in a variety of ways including evaluating performance and designing offensive strategies. This study proposed a novel framework that uses the events preceding a shot, to improve the accuracy of the expe...

Low back pain (LBP) is a leading cause of disability worldwide, with up to 25% of cases become chronic (cLBP). Optimal diagnostic tools for cLBP remains unclear. Here we leveraged a comprehensive multidimensional dataset and machine learning based feature importance selection to identify the most effective diagnostic tools for cLBP patient stratifi...

Epilepsy is a life-threatening neurological condition. Manual detection of epileptic seizures (ES) is laborious and burdensome. Machine learning techniques applied to electroencephalography (EEG) signals are widely used for automatic seizure detection. Some key factors are worth considering for the real-world applicability of such systems: (i) cont...

Diabetes is one of the leading non-communicable diseases globally, adversely impacting an individual’s quality of life and adding a considerable burden to the healthcare systems. The necessity for frequent blood glucose (BG) monitoring and the inconveniences associated with self-monitoring of BG, such as pain and discomfort, has motivated the devel...

Association football (commonly known as football or soccer) in the modern era places a greater emphasis on collaborating and working together as a team instead of relying solely on individual skills to strategize winning performances. The low-scoring and unpredictable nature of association football makes evaluating team performances challenging. Sp...

Aims Heart failure is a serious condition that often goes undiagnosed in primary care due to the lack of reliable diagnostic tools and the similarity of its symptoms with other diseases. Non‐invasive monitoring of heart rate variability (HRV), which reflects the activity of the autonomic nervous system, could offer a novel and accurate way to detec...

Background Sleep disorders, such as insomnia, have been associated with extended periods of inactive, sedentary behaviour. Many factors contribute to insomnia, including stress, irregular sleep patterns, mental health issues, inadequate sleeping schedules, diseases, neurological disorders and prescription medications. Objectives Identification of...

This paper presents the implementation and evaluation of the ant colony optimisation with adaptive building blocks, an approach designed to improve the performance of the ant colony optimisation algorithm by selecting self-adaptive building blocks through Elitist, Roulette, and Hybrid (combination between Elitist and Roulette) selection strategies....

In patients presenting with low back pain (LBP), once specific causes are excluded (fracture, infection, inflammatory arthritis, cancer, cauda equina and radiculopathy) many clinicians pose a diagnosis of non-specific LBP. Accordingly, current management of non-specific LBP is generic. There is a need for a classification of non-specific LBP that i...

The classification of non-specific chronic low back pain (CLBP) according to multidimensional data could guide clinical management; yet recent systematic reviews show this has not been attempted. This was a prospective cross-sectional study of participants with CLBP (n = 21) and age-, sex- and height-matched pain-free controls (n = 21). Nervous sys...

BACKGROUND Approximately 25% of prediabetics progress to overt type 2 diabetes within 3 to 5 years and 70% develop overt diabetes in their lifetime. Prediabetics could be identified through screening, which could reduce the healthcare burden. HRV is an index of the autonomic nervous system and serves as a measurable indicator for various chronic di...

Most gait parameters decrease with age and are even more importantly reduced with frailty. However, other gait parameters exhibit different or even opposite trends for aging and frailty, and the underlying reason is unclear. Literature focuses either on aging, or on frailty, and a comprehensive understanding of how biomechanical gait regulation evo...

The advances of 5G and the Internet of Things enable more devices and sensors to be interconnected. Unlike traditional data, the large amount of data generated from various sensors and devices requires real-time analysis. The data objects in a stream will change over time and only have a single access. Thus, traditional methods no longer meet the n...

We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and...

Acute and chronic insomnia have different causes and may require different treatments. They are investigated with multi-night nocturnal actigraphy data from two sleep studies. Two different wrist-worn actigraphy devices were used to measure physical activities. This required data pre-processing and transformations to smooth the differences between...

We consider a model of adversarial dynamics consisting of three populations, labelled Blue, Green, and Red, which evolve under a system of first order nonlinear differential equations. Red and Blue populations are adversaries and interact via a set of Lanchester combat laws. Green is divided into three sub-populations: Red supporters, Blue supporte...

Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical decision making. Machine learning can build upon prior sub-grouping approaches by using a data-driven approach to overcome clinician subjectivity, however, only binary classification of pain versus no-pain has been attempted to date. In our cross-sectional stu...

We consider a model of adversarial dynamics consisting of three populations, labelled Blue, Green and Red, which evolve under a system of first order nonlinear differential equations. Red and Blue populations are adversaries and interact via a set of Lanchester combat laws. Green is divided into three sub-populations: Red supporters, Blue supporter...

Cardiovascular diseases (CVD) are the leading cause of mortality globally. Despite improvement in therapies, people with CVD lack support for monitoring and managing their condition at home and out of hospital settings. Smart Home Technologies have potential to monitor health status and support people with CVD in their homes. We explored the Smart...

Disease screening identifies a disease in an individual/community early to effectively prevent or treat the condition. COVID-19 has restricted hospital visits for screening and other healthcare services resulting in the disruption of screening for cancer, diabetes, and cardiovascular diseases. Smartphone technologies, coupled with built-in sensors...

In recent years, artificial intelligence technologies have been successfully applied in time series prediction and analytic tasks. At the same time, a lot of attention has been paid to financial time series prediction, which targets the development of novel deep learning models or optimize the forecasting results. To optimize the accuracy of stock...

In this study, we used grammatical evolution to develop a customised particle swarm optimiser by incorporating adaptive building blocks. This makes the algorithm self-adaptable to the problem instance. Our objective is to provide the means to automatically generate novel population-based meta-heuristics by scoring the building blocks. We propose a...

This paper presents a novel similarity measure to identify interesting traffic patterns on a large traffic flow time series data for the central suburbs of Melbourne city in Australia. This new measure is a weighted Dynamic Time Warping (DTW) method based on Gaussian probability function, named GWDTW, that reflects the relative importance of peak h...

Physiological signals like Electrocardiography (ECG) and Electroencephalography (EEG) are complex and nonlinear in nature. To retrieve diagnostic information from these, we need the help of nonlinear methods of analysis. Entropy estimation is a very popular approach in the nonlinear category, where entropy estimates are used as features for signal...

This paper focuses on density-based clustering, particularly the Density Peak (DP) algorithm and the one based on density-connectivity DBSCAN; and proposes a new method which takes advantage of the individual strengths of these two methods to yield a density-based hierarchical clustering algorithm. We first formally define the types of clusters DP...

We propose a novel machine learning-based method for analysing multi-night actigraphy signals to objectively classify and differentiate nocturnal awakenings in individuals with chronic insomnia (CI) and their cohabiting healthy partners. We analysed nocturnal actigraphy signals from 40 cohabiting couples with one partner seeking treatment for insom...

We consider a model of three interacting sets of decision-making agents, labeled Blue, Green and Red, represented as coupled phased oscillators subject to frustrated synchronisation dynamics. The agents are coupled on three networks of differing topologies, with interactions modulated by different cross-population frustrations, internal and cross-n...

A two-dimensional system of differential equations with delay modelling the glucose-insulin interaction processes in the human body is considered. Sufficient conditions are derived for the unique positive equilibrium in the system to be globally asymptotically stable. They are given in terms of the global attractivity of the fixed point in a limiti...

The problem of inhomogeneous cluster densities has been a long-standing issue for distance-based and density-based algorithms in clustering and anomaly detection. These algorithms implicitly assume that all clusters have approximately the same density. As a result, they often exhibit a bias towards dense clusters in the presence of sparse clusters....

The aim of this paper is to investigate the cardiorespiratory synchronization in athletes subjected to extreme physical stress combined with a cognitive stress tasks. ECG and respiration were measured in 14 athletes before and after the Ironman competition. Stroop test was applied between the measurements before and after the Ironman competition to...

In this paper, a model based on a system of delay differential equations, describing a process of glucose-insulin regulation in the human body, is studied numerically. For simplicity, the system is based on a single delay due to the practical importance of one of the two delays appearing in more complex models. The stability of the system is invest...

The aim of this paper is to investigate the cardiorespiratory synchronization in athletes subjected to extreme physical stress combined with a cognitive stress tasks. ECG and respiration were measured in 14 athletes before and after the Ironmen competition. Stroop test was applied between the measurements before and after the Ironmen competition to...

We consider a model of three interacting sets of decision-making agents, labeled Blue, Green and Red, represented as coupled phased oscillators subject to frustrated synchronisation dynamics. The agents are coupled on three networks of differing topologies, with interactions modulated by different cross-population frustrations, internal and cross-n...

Knowledge of optimal technical performance is used to determine match strategy and the design of training programs. Previous studies in men’s soccer have identified certain technical characteristics that are related to success. These studies however, have relative limited sample sizes or limited ranges of performance indicators, which may have limi...

A two-dimensional system of differential equations with delay modelling the glucose-insulin interaction processes in the human body is considered. Sufficient conditions are derived for the unique positive equilibrium in the system to be globally asymptotically stable. They are given in terms of the global attractivity of the fixed point in a limiti...

Artificial intelligence and machine learning (AI/ML) could enhance the ability to detect patterns of clinical characteristics in low-back pain (LBP) and guide treatment. We conducted three systematic reviews to address the following aims: (a) review the status of AI/ML research in LBP, (b) compare its status to that of two established LBP classific...

Shapelets are subsequences of time-series that represent local patterns and can improve the accuracy and the interpretability of time-series classification. The major task of time-series classification using shapelets is to discover high quality shapelets. However, this is challenging since local patterns may have various scales/lengths rather than...

Characterising the behaviour of solutions in nonlinear delay-differential equations can be mathematically challenging due to their nonlinear structure and non-local nature. Their appearance in many applied fields is in great part due to their ability to model dynamics with non-instantaneous effects, which could not be described by the associated n...

Team sports can be viewed as dynamical systems unfolding in time and thus require tools and approaches congruent to the analysis of dynamical systems. The analysis of the pattern-forming dynamics of player interactions can uncover the clues to underlying tactical behaviour. This study aims to propose quantitative measures of a team’s performance de...

In this paper we propose a new machine learning model for classification of nocturnal awakenings in acute insomnia and normal sleep. The model does not require sleep diaries or any other subjective information from the individuals who took part of the study. It is based on nocturnal actigraphy collected from pre-medicated individuals with acute ins...

The Internet of Things (IoT) has gained significant recognition to become a novel sensing paradigm to interact with the physical world in this Industry 4.0 era. The IoTs are being used in many diverse applications that are part of our life and is growing to become the global digital nervous systems. It is quite evident that in the near future, hund...

This paper addresses reliable and efficient calculation of the mode of a multivariate sample, which is a classical fusion function. In particular, we focus on the inputs given on the unit simplex, when aggregating elements of Atanassov intuitionistic fuzzy sets, interval‐valued fuzzy sets and their extensions, as well as compositional data. We outl...

Time series classification is important due to its pervasive applications, especially for the emerging Smart City applications that are driven by intelligent sensors. Shapelets are sub-sequences of time series that have highly predictive abilities, and time series represented by shapelets can better reveal the patterns thus have better classificati...

Over a few decades, there is a steady accretion of life expectancy in many countries. Significant advances in modern healthcare technologies, medicines and overall health care awareness gave many to lead a prolonged healthy life. Over the past few years, there has been a huge demand for unobtrusive health monitoring systems from both medical profes...

Existing physiological control fatigue models propose that there may be a regulator in the central nervous system which modulates our daily physical activity. Within limits, this regulator ensures physical activity is completed without physiological system failure through interactive communications between the peripheral systems and the central sys...

We propose a computationally efficient natural neighbour based metric for discovering clusters of arbitrary shape based on fuzzy measures. The approximate natural neighbours are found with the help of the Choquet integral with respect to a specially designed two-additive fuzzy measure. Fuzzy betweenness relation is used to construct such a measure...

Glucose regulation is an essential function of the human body which enables energy to be effectively utilized by the brain, organs and muscles. This regulation operates in a cyclic manner, in different periodic regimes. Indeed, ultradian rhythms with a period of 70 to 150 minutes have been clinically observed in healthy patients under various gluco...

Medical prognosis is based on symptoms, such as loss of functionality or a deviation of the average value of physiological parameters from their adequate homeostatic ranges. On the other hand, alterations in physiological regulation may precede the appearance of symptoms, as has been suggested in geriatrics in the case of age-associated frailty. Te...

The article focuses on specific aspects of Georgi Markovski’s fiction, linking them with the influence of magical realism over his work. The analysis is based on the author’s debut novel Sensemaya (1971) and its version from 1978, named Portrait with a blue bird.

Experimental studies of the flowering of Arabidopsis thaliana have shown that a large complex gene regulatory network (GRN) is responsible for its regulation. This process has been mathematically modelled with deterministic differential equations by considering the interactions between gene activators and inhibitors (Valentim et al. in PLoS ONE 10(...

This paper focuses on density-based clustering, particularly the Density Peak (DP) algorithm and the one based on density-connectivity DBSCAN; and proposes a new method which takes advantage of the individual strengths of these two methods to yield a density-based hierarchical clustering algorithm. Our investigation begins with formally defining th...

Many distance-based algorithms exhibit bias towards dense clusters in inhomogeneous datasets (i.e., those which contain clusters in both dense and sparse regions of the space). For example, density-based clustering algorithms tend to join neighbouring dense clusters together into a single group in the presence of a sparse cluster; while distance-ba...

Density-based clustering is able to find clusters of arbitrary sizes and shapes while effectively separating noise. Despite its advantage over other types of clustering, it is well-known that most density-based algorithms face the same challenge of finding clusters with varied densities. Recently, ReScale, a principled density-ratio preprocessing t...

Telecare is the use of devices installed in homes to deliver health and social care to the elderly and infirm. The aim of this paper is to identify patterns of use for different devices and associations between them. The data were provided by a telecare call centre in the North East of England. Using statistical analysis and machine learning, we an...

Circadian rhythms become less dominant and less regular with chronic-degenerative disease, such that to accurately assess these pathological conditions it is important to quantify not only periodic characteristics but also more irregular aspects of the corresponding time series. Novel data-adaptive techniques, such as singular spectrum analysis (SS...

We study the effect of diabetic deficiencies on the production of an oscillatory ultra-dian regime using a deterministic nonlinear model which incorporates two physiological delays. It is shown that insulin resistance impairs the production of oscillations by dampening the ultradian cycles. Four strategies for restoring healthy regulation are explo...

The aim of this study is to investigate the stability properties of a model of the lac operon enhanced with stochastic perturbations. New sufficient conditions of exponential mean square stability are obtained analytically for this model and threshold values derived. For regulatory networks, an observer method for the dynamic of the lac operon mode...

This work focuses on methods for investigation of physiological time series based on complexity analysis. It is a part of a wider programme to determine non-invasive markers for healthy ageing. We consider two case studies investigated with actigraphy: (a) sleep and alternations with insomnia, and (b) ageing effects on mobility patterns. We illustr...

In this paper, a two-delay model for the ultradian oscillatory behaviour of the glucose-insulin regulation system is studied. Hill functions are introduced to model nonlinear physiological interactions within this system and ranges on parameters reproducing biological oscillations are determined on the basis of analytical and numerical consideratio...

For the first time, fractal analysis techniques are implemented to study the correlations present in sleep actigraphy for individuals suffering from acute insomnia with comparisons made against healthy subjects. Analysis was carried out for 21 healthy individuals with no diagnosed sleep disorders and 26 subjects diagnosed with acute insomnia during...

Generalized net (GN) model of telemedicine/telehealth based on body temperature sensors is proposed. In a previous paper, GN that describes the connection between sensors and remote server was proposed. In the present model, the focus is on the process of decision making in the telemedicine/telehealth center.

This paper reports the experimental wavelet denoising techniques carried out for the first time for a number of modulation schemes for indoor optical wireless communications in the presence of fluorescent light interference. The experimental results are verified using computer simulations, clearly illustrating the advantage of the wavelet denoising...

Clustering techniques have been widely used for gene expression data analysis. However, noise, high dimension and redundancies are serious issues, making the traditional clustering algorithms sensitive to the choice of parameters and initialization. Therefore, the results lack stability and reliability. In this paper, we propose a novel clustering...

The study's objective is to justify the use of the ANN for the short-term prediction of share prices, particularly in the banking sector. The assumption is that financial share time-series contain significant non-linearity and that the ANN can be utilized effectively. The ANN model is compared with a linear regression model. Non-linearity is shown...

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Automatic off-line Arabic handwriting recognition based on segmentation still faces big challenges. A database, covering all shapes of handwritten Arabic characters, is required to facilitate the recognition process. This paper introduces a new database for handwritten Arabic characters (HACDB), designed to cover all shapes of Arabic characters inc...

Intuitionistic fuzzy logic (IFL) has been implemented in this investigation aiming to derive intuitionistic fuzzy estimations of S. cerevisiae fed-batch cultivation model parameters obtained using standard simple (SGA) and multi-population (MpGA) genetic algorithms. Performances of MpGA have been tested before and after the application of the proce...

A Viterbi algorithm (VA) is the optimal decoding strategy for the convolutional code. The Viterbi algorithm is complex and requires a large memory and delay. In this paper, an alternative sub-optimal decoder based on the artificial neural network (ANN) is proposed and studied using a sliding block decoding algorithm. The ANN is trained in a supervi...

In this paper, we construct generalized quantum states for systems with finite discrete spectrum and compare the behavior of those states with the classical analogs. Phase-space trajectories are analyzed in the classical and quantum cases. We focus on the following bounded anharmonic exactly solvable one-dimensional potentials: Morse, hyperbolic Pö...